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of 21
pro vyhledávání: '"Dathathri, Roshan"'
Autor:
Hoang, Loc, Agarwal, Udit, Gill, Gurbinder, Dathathri, Roshan, Seal, Abhik, Martin, Brian, Pingali, Keshav
Graph transformer networks (GTN) are a variant of graph convolutional networks (GCN) that are targeted to heterogeneous graphs in which nodes and edges have associated type information that can be exploited to improve inference accuracy. GTNs learn i
Externí odkaz:
http://arxiv.org/abs/2106.08500
Graph pattern mining (GPM) is used in diverse application areas including social network analysis, bioinformatics, and chemical engineering. Existing GPM frameworks either provide high-level interfaces for productivity at the cost of expressiveness o
Externí odkaz:
http://arxiv.org/abs/2011.03135
Autor:
Dathathri, Roshan, Kostova, Blagovesta, Saarikivi, Olli, Dai, Wei, Laine, Kim, Musuvathi, Madanlal
Publikováno v:
Programming Language Design and Implementation (PLDI 2020) 546-561
Fully-Homomorphic Encryption (FHE) offers powerful capabilities by enabling secure offloading of both storage and computation, and recent innovations in schemes and implementations have made it all the more attractive. At the same time, FHE is notori
Externí odkaz:
http://arxiv.org/abs/1912.11951
Autor:
Jatala, Vishwesh, Hoang, Loc, Dathathri, Roshan, Gill, Gurbinder, Nandivada, V Krishna, Pingali, Keshav
Load-balancing among the threads of a GPU for graph analytics workloads is difficult because of the irregular nature of graph applications and the high variability in vertex degrees, particularly in power-law graphs. We describe a novel load balancin
Externí odkaz:
http://arxiv.org/abs/1911.09135
There is growing interest in graph pattern mining (GPM) problems such as motif counting. GPM systems have been developed to provide unified interfaces for programming algorithms for these problems and for running them on parallel systems. However, ex
Externí odkaz:
http://arxiv.org/abs/1911.06969
Autor:
Gill, Gurbinder, Dathathri, Roshan, Maleki, Saeed, Musuvathi, Madan, Mytkowicz, Todd, Saarikivi, Olli
Many applications today, such as NLP, network analysis, and code analysis, rely on semantically embedding objects into low-dimensional fixed-length vectors. Such embeddings naturally provide a way to perform useful downstream tasks, such as identifyi
Externí odkaz:
http://arxiv.org/abs/1909.03359
Intel Optane DC Persistent Memory (Optane PMM) is a new kind of byte-addressable memory with higher density and lower cost than DRAM. This enables the design of affordable systems that support up to 6TB of randomly accessible memory. In this paper, w
Externí odkaz:
http://arxiv.org/abs/1904.07162
Autor:
Dathathri, Roshan, Saarikivi, Olli, Chen, Hao, Laine, Kim, Lauter, Kristin, Maleki, Saeed, Musuvathi, Madanlal, Mytkowicz, Todd
Fully Homomorphic Encryption (FHE) refers to a set of encryption schemes that allow computations to be applied directly on encrypted data without requiring a secret key. This enables novel application scenarios where a client can safely offload stora
Externí odkaz:
http://arxiv.org/abs/1810.00845
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